Forecasting domestic credit growth based on ARIMA model: Evidence from Vietnam and China

Dinh, Doan Van

doi:10.5267/j.msl.2019.11.010

Cited by 21 publications

(11 citation statements)

References 6 publications

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“…Endogenous variable impact analysis is to assess the volatility of oil prices itself and economic growth, the events of 2008 showed that the volatility of oil prices is a source of exogenous volatility, but influences Financial benefit is an endogenous variable. Besides, the oil-rich countries have the impact of their financial crisis when their economic growth has depended on continuously falling oil prices (Uchechukwu et al, 2019;Dinh, 2020c).…”

Section: Literature Reviewmentioning

confidence: 99%

Impact of Crude Oil Price on Countries’ and Vietnam’s GDP Growth: Variance Decomposition Approach

Dinh¹

2021

IJEEP

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The crude oil price fluctuation investigation is to explore the impact of crude oil price shocks on the countries' economic growth. The Vector Autoregressive Model (VAR) was applied and the variance decomposition is to analyze the impact of the GDP growth due to the shock of the crude oil price. Besides, nine countries' data were collected from 1990 to the third quarter of 2020. The countries' GDP growth was impacted by the crude oil price in 5 years respectively: 44.98%; 40.03%; 31.06%; 32.27%; 33.21%; 36.03%; 27.79%; 15.35%; 40.75% of the following countries are: China; America; Japan; Korea; Singapore; Thailand; Indonesia; Vietnam; Malaysia. This study identifies issues for countries to consider: have a comprehensive solution among macroeconomic policies, monetary policy, fiscal policy and other policies to control and stimulate growth.

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Section: Literature Reviewmentioning

confidence: 99%

Impact of Crude Oil Price on Countries’ and Vietnam’s GDP Growth: Variance Decomposition Approach

Dinh¹

2021

IJEEP

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“…ℎ = 2,3, … , 𝑛𝑛, where h and n are the forecasting horizon and the number of out-of-sample time series data. Therefore, the forecasting horizons that have been applied in the study are 2, 3, 4, 5, 7, 10, 15, 20, 25, 30 and 45-days ahead of the overnight IIR [6][7] and [16][17][18][19]. Consequently, a (1 − 𝛼𝛼)100% PIs for h-step ahead forecasting and 𝑎𝑎 𝑡𝑡 follows normal distribution is given by Equation 11.…”

Section: Stage Iv: Forecastingmentioning

confidence: 99%

Forecasting Malaysian overnight islamic interbank rate using the Box-Jenkins model

Radzi

Yaziz

2021

DAAM

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Modelling the overnight Islamic interbank rate (IIR) is imperative to define the IIR performance as it would help the Islamic banks to adjust its costs of funding effectively and facilitate the policy makers to regulate a comprehensive monetary policy in Malaysia. The IIR framework which has been regulated by Bank Negara Malaysia under dual banking and financial system has always been overlooked in most previous studies in modelling the financial instruments rates. Therefore, it is vital to select the appropriate model as it resembles with the features of the IIR. The study assesses the forecasting performance of overnight IIR using the Box-Jenkins model. The suggested Box-Jenkins model has been applied to the Malaysian overnight IIR (in percentage) from 02/01/2001 to 31/12/2020. The empirical results determine that ARIMA (0,1,1) is the most appropriate model in forecasting overnight IIR as the model provides the smallest Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). In multistep ahead forecasting, it can be summarised that ARIMA (0,1,1) model is able to trail the actual data trend of daily Malaysian overnight IIR up to 5-day ahead within 95% prediction intervals.

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“…Regression analysis is like other deductive methods. The objective of the paper is to collect a random sample from the GDP growth and inflation rate and use it to estimate their characteristic (Dinh, 2020a).…”

Section: Literature Reviewmentioning

confidence: 99%

Impulse Response of Inflation to Economic Growth Dynamics: VAR Model Analysis

Dinh¹

2020

JAFEB

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The study investigates the impact of inflation rate on economic growth to find the best-fit model for economic growth in Vietnam. The study applied Vector Autoregressive (VAR), cointegration models, and unit root test for the time-series data from 1996 to 2018 to test the inflation impact on the economic growth in the short and long term. The study showed that the two variables are stationary at lag first difference I(1) with 1%, 5% and 10%; trace test indicates two cointegrating equations at the 0.05 level, the INF does not granger cause GDP, the optimal lag I(1) and the variables are closely related as R2 is 72%. It finds that the VAR model's results are the basis to perform economic growth; besides, the inflation rate is positively related to economic growth. The results support the monetary policy. This study identifies issues for Government to consider: have a comprehensive solution among macroeconomic policies, monetary policy, fiscal policy and other policies to control and maintain the inflation and stimulate growth; set a priority goal for sustainable economic growth; not pursue economic growth by maintaining the inflation rate in the long term, but take appropriate measures to stabilize the inflation at the best-fitted VAR forecast model.

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Forecasting domestic credit growth based on ARIMA model: Evidence from Vietnam and China

Cited by 21 publications

References 6 publications

Impact of Crude Oil Price on Countries’ and Vietnam’s GDP Growth: Variance Decomposition Approach

Impact of Crude Oil Price on Countries’ and Vietnam’s GDP Growth: Variance Decomposition Approach

Forecasting Malaysian overnight islamic interbank rate using the Box-Jenkins model

Impulse Response of Inflation to Economic Growth Dynamics: VAR Model Analysis

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